Oxygen Perfusion (Persufflation) of Human Pancreata Enhances Insulin Secretion and Attenuates Islet Proinflammatory Signaling
Bibliographic record
Abstract
BACKGROUND: All human islets used in research and for the clinical treatment of diabetes are subject to ischemic damage during pancreas procurement, preservation, and islet isolation. A major factor influencing islet function is exposure of pancreata to cold ischemia during unavoidable windows of preservation by static cold storage (SCS). Improved preservation methods may prevent this functional deterioration. In the present study, we investigated whether pancreas preservation by gaseous oxygen perfusion (persufflation) better preserved islet function versus SCS. METHODS: Human pancreata were preserved by SCS or by persufflation in combination with SCS. Islets were subsequently isolated, and preparations in each group matched for SCS or total preservation time were compared using dynamic glucose-stimulated insulin secretion as a measure of β-cell function and RNA sequencing to elucidate transcriptomic changes. RESULTS: Persufflated pancreata had reduced SCS time, which resulted in islets with higher glucose-stimulated insulin secretion compared to islets from SCS only pancreata. RNA sequencing of islets from persufflated pancreata identified reduced inflammatory and greater metabolic gene expression, consistent with expectations of reducing cold ischemic exposure. Portions of these transcriptional responses were not associated with time spent in SCS and were attributable to pancreatic reoxygenation. Furthermore, persufflation extended the total preservation time by 50% without any detectable decline in islet function or viability. CONCLUSIONS: These data demonstrate that pancreas preservation by persufflation rather than SCS before islet isolation reduces inflammatory responses and promotes metabolic pathways in human islets, which results in improved β cell function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".